Is my Neural Network program fully connected?
Is figure = code?

No.
Your figure shows a fully connected feed forward network (MLP). But in your code you are using a two layer LSTM with peepholes. For the visualization of LSTMs, blocks are usually used for each layer.

Here is a figure of the LSTM with peepholes which is the base of the tensorflow implementation (Source: Paper, fig. 1).





Why size 86?

The input is concatenated with the hidden state:
n_inputs + n_neurons = 36 + 50 = 86.
Why size 100 in the second layer?

The second LSTM layer gets input of size 50 by the first layer (n_neurons) which is concatenated with the hidden state of the second layer (of size n_neurons = 50).
Therefore you get 50 + 50 = 100.
Why size 200?

There are four weight matrices of size $86 \times 50$ (fig.: colored circles and the g circle), which seem to be combined to one matrix ($4 \cdot 50$) of size $86 \times 200$ (layer0/kernel).
Why size 50?

The three variables w_f_diag, w_i_diag and w_o_diag are for the peephole connections (fig: dashed lines) and they have the size of n_neurons = 50.